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with ONNX Runtime brings flexible, efficient AI customization by enabling easy integration of LoRA adapters for dynamic, personalized models with minimal resource demands.', + link: 'blogs/multilora', + image: MultiLoraThumbnail, + imgalt: 'Serving LoRA models separately vs with MultiLoRA' + }, { title: 'Is it better to quantize before or after finetuning?', @@ -69,6 +80,8 @@ image: GoodnotesThumbnail, imgalt: 'Scribble to Erase feature on Goodnotes for Windows, Web, and Android' }, + ]; + let blogs = [ { title: 'Democratizing AI Model optimization with the new Olive CLI', date: 'November 11th, 2024', @@ -77,9 +90,7 @@ link: 'blogs/olive-cli', image: OliveCli, imgalt: 'Olive Flow' - } - ]; - let blogs = [ + }, { title: 'Enhancing team collaboration during AI model optimization with the Olive Shared Cache', diff --git a/src/routes/blogs/multilora/+page.svx b/src/routes/blogs/multilora/+page.svx index 83f4e35163a90..c04f4e1b4a5a8 100644 --- a/src/routes/blogs/multilora/+page.svx +++ b/src/routes/blogs/multilora/+page.svx @@ -1,6 +1,6 @@ --- -title: 'Announcing MultiLoRA with ONNX Runtime: Revolutionizing AI Customization ' -date: '19th November, 2024' +title: 'Announcing MultiLoRA with ONNX Runtime: Revolutionizing AI Customization' +date: '20th November, 2024' description: 'MultiLoRA with ONNX Runtime brings flexible, efficient AI customization by enabling easy integration of LoRA adapters for dynamic, personalized models with minimal resource demands.' keywords: 'MultiLoRA, LoRA, ONNX Runtime, AI customization, LoRA adapters, Olive toolchain, large language models, model personalization, model optimization, Hugging Face, AI deployment, AI performance' authors: ['Dmitri Smirnov', 'Jambay Kinley', 'Natalie Kershaw', 'Parinita Rahi', 'Pranav Sharma', 'Devang Patel', 'Samuel Kemp']